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Integrating AI with Java: Quarkus and Langchain4j
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Manage episode 409818457 series 2469611
Dimitris appeared previously on "#64 Quarkus 1.0 and SpringBoot", discussion about integrating AI language models (LLMs) with Java applications using quarkus and langchain4j, OpenShift AI, the benefits of using Quarkus for AI integration, Drools and ML, the potential of using AI for rule engines and decision making, the challenges of handling state and context with LLMs, InfiniSpan and vector databases, the role of vector stores and embeddings for semantic search, the advantages of Java for enterprise applications and maintenance, the potential of using AI models natively with GraalVM, the importance of tools functionality for LLMs to call Java methods, the excitement around AI in the Java community, the future trajectory of tighter integration between Java and AI models, the potential of using AI for code generation and intelligent developer tooling
Dimitris Andreadis on twitter: @dandreadis
339 episodi
Fetch error
Hmmm there seems to be a problem fetching this series right now. Last successful fetch was on March 23, 2025 17:41 (
What now? This series will be checked again in the next day. If you believe it should be working, please verify the publisher's feed link below is valid and includes actual episode links. You can contact support to request the feed be immediately fetched.
Manage episode 409818457 series 2469611
Dimitris appeared previously on "#64 Quarkus 1.0 and SpringBoot", discussion about integrating AI language models (LLMs) with Java applications using quarkus and langchain4j, OpenShift AI, the benefits of using Quarkus for AI integration, Drools and ML, the potential of using AI for rule engines and decision making, the challenges of handling state and context with LLMs, InfiniSpan and vector databases, the role of vector stores and embeddings for semantic search, the advantages of Java for enterprise applications and maintenance, the potential of using AI models natively with GraalVM, the importance of tools functionality for LLMs to call Java methods, the excitement around AI in the Java community, the future trajectory of tighter integration between Java and AI models, the potential of using AI for code generation and intelligent developer tooling
Dimitris Andreadis on twitter: @dandreadis
339 episodi
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